The intelligent planning and scheduling system developed by UHAlean based on the optimization algorithm engine helps Bosch-Hasco to achieve flexible decision-making and digital management of scheduling in a multi-objective, multi-constrained and dynamic environment with a goal to improve production efficiency and reduce production costs, paving the way for Bosch-Hasco to establish a flexible and intelligent supply chain.

By combining with modeling solutions and big data processing, UHAlean makes production scheduling plans for ATL-ND, including Dongguan and Ningde four main production areas: balancing the total annual market demand, production capacity, material supply and other production resources, providing daily planning guidance, logistics demand planning, capacity planning, and realizing lean planning and management of man-machine process material loop.

The construction of the oil and gas value chain optimization system will support CNPC's natural gas production and operation plan optimization, achieve the overall optimization of the natural gas value chain, and enhance the optimal allocation of CNPC's natural gas resources and its capacity for production, operation and management.

Through integration of advanced algorithms such as heuristic algorithms, intelligent optimization algorithms, and modeling solutions, it builds a collaborative production system linking the scheduling plans of general assembly and partial assembly branches, and develop medium- and long-term master plans and short-term daily plans to achieve various business goals such as reducing changeovers, material alignment checks, and decreasing the amount of stockpiles.

The supply chain warehouse network planning project jointly built by Haier and UHAlean helps Haier realize unified planning and management of the group's warehouse network layout through intelligent warehouse site selection, warehouse forecasting, inventory allocation optimization, and warehouse resource performance management for the entire supply chain process.

UHAlean helps Xinyi Glass to build an efficient and collaborative supply chain system with overall planning, including business architecture, planning system, and data and application architecture, which realizes the end-to-end comprehensive collaboration and transparency of the whole process, enhancing market competitiveness, reduces production costs, improving the productivity of a single factory, and makes the supply chain a new engine of competitiveness for the company.

The implementation of the intelligent transportation path optimization project reduces scheduling time from hours to minutes and increases transportation efficiency by 92%, significantly improving dispatcher efficiency and consistently reducing logistics transportation costs.

UHAlean helps Luxshare integrate order data and process data by interfacing with existing ERP and MES systems to perform full process calculations for all orders and obtain accurate lead times. The calculation efficiency has been improved by 120 times, and the new system supports 3 targets in just 1 minute. Through multi-process collaboration, the overall production lead time is shortened by 40%, and the order delivery on-time rate is improved from 60% to 86%.

Relying on UHAlean's Transport Optimization Scheduling, TOS system, Danone starts its digital transformation and achieves accuracy and speed in its transportation business, reducing the hours of manual scheduling (scheduling) to 8 minutes, lowering total delivery costs by 6% and total trips by 15%-25%.

In view of business constraints such as material, capacity, order delivery, and work-in-process inventory, it outputs daily scheduling plans that are accurate down to the minute, while achieving the three goals of maximizing capacity utilization, maximizing order delivery, and minimizing product and work-in-process inventory.

UHAlean helps this company with overall planning through an efficient and collaborative supply chain system, which realizes the need for centralized business integration of plants, regions, and groups, and carries out multi-scenario simulation and optimization of production by taking into account various constraints. It achieves the effect of minimizing cost, energy emission and switching time, maximizing delivery rate and unit utilization, and using production lines in a balanced manner.

Co-developing urban rail transit crew system based on UHAlean's powerful algorithm engine is in line with the current business model, which effectively improves the utilization of rail crew's working hours, and increases the effective working hour rate by 5%-10%.

UHAlean helps Xiamen Airlines build a new generation of "intelligent decision-based, human intervention-supported" decision support system to achieve accurate real-time forecasting of flight revenue in the next 90 days, and combines with optimization algorithms to guide flight planning. The system has accumulated more than 10 million flights and provided more than 10 million marginal contributions.

Through UHAlean's route network planning, automated management of route flights is achieved. Meanwhile, algorithms are used to optimize and improve the model aircraft utilization effectiveness by 2%, and the global route scheduling time is reduced from hours to minutes.

UHAlean's aircrew scheduling system helps China Eastern Airlines reduce 90% of its automated crew pairing time to within 5 minutes, increase the average daily flight hours of crew by 10%, and reduce the number of crew on duty required daily by 10%. This has not only significantly improved the personnel utilization rate of China Eastern Airlines, but also effectively reduces the cost of overnight flight crew.